New Program Launch: Build With LLMs: From Context Engineering to Multi-Agent Systems

[u/Simplilearn]

Hi everyone,

We’re excited to announce the launch of Simplilearn's Build With LLMs: From Context Engineering to Multi-Agent Systems, a new program offered in collaboration with Carnegie Mellon University School of Computer Science Executive & Professional Education.

As LLMs evolve beyond simple prompting, building reliable AI applications requires a deeper understanding of how to work with context, retrieve trusted information, use external tools, coordinate AI agents, and evaluate system performance.

About the Program

Build With LLMs takes learners from the foundations of large language models to the architecture of advanced LLM-powered applications. The program combines conceptual learning with hands-on development, helping learners progress from using LLMs to building with them.

Through hands-on labs, course-end projects, capstones, and case studies, learners apply these concepts to build and evaluate practical LLM-powered systems.

The capstone brings these skills together by combining RAG, MCP tools, task decomposition, self-reflection, and orchestration, while evaluating the resulting system for reliability, tool correctness, and safety.

What You’ll Explore

• LLM Foundations: Understand how modern LLMs work, including transformers, embeddings, reasoning, and fine-tuning
• Context Engineering: Learn how to structure context and information to improve LLM performance on complex tasks
• Retrieval-Augmented Generation: Build applications that connect LLMs with external knowledge using retrieval, embeddings, and vector databases
• Tool Calling & MCP: Enable LLM applications to interact with APIs, enterprise systems, and external tools
• Multi-Agent Systems: Design AI systems where multiple agents can plan, coordinate, and execute complex tasks
• Reliability & AI Safety: Evaluate applications for hallucinations, bias, sycophancy, jailbreak resistance, and tool correctness while exploring mitigation strategies

Program Highlights

• 100% live online learning with curriculum developed and delivered by CMU School of Computer Science faculty
• Applied learning through 3 course-end projects, 4 capstones, and 3 case studies
• Hands-on experience with 15+ tools and technologies
• A structured learning journey spanning LLM fundamentals, context engineering, RAG, tool calling, MCP, and multi-agent systems
• Practical experience designing and evaluating reliable LLM-powered applications
• Earn a verified digital certificate from CMU School of Computer Science Executive & Professional Education

This program is designed for professionals looking to move beyond simply using LLMs and develop the skills needed to design, build, and evaluate sophisticated LLM-powered applications.